Epidemiology of transthyretin (ATTR) amyloidosis: a systematic literature review
Bibliographic record
Abstract
Abstract Introduction Significant advances in the treatment of transthyretin (ATTR) amyloidosis has led to an evolving understanding of the epidemiology of this condition. This systematic literature review (SLR) aims to synthesize current evidence on epidemiology and mortality outcomes in ATTR amyloidosis, addressing the need for a comprehensive understanding of its current global impact. Methods An SLR of the literature from January 2018 to April 2023 was conducted using the Medline and Embase databases. The review followed the PRISMA guidelines. Studies evaluating populations with genotypes and phenotypes of ATTR amyloidosis (variant and wild-type cardiomyopathy, polyneuropathy, and mixed) were included. Observational studies, systematic reviews, and meta-analyses were eligible, while reports, commentaries, clinical trials, and non-ATTR amyloidosis studies were excluded. Extracted data included prevalence, incidence, and mortality rates. Results Of the 1,458 studies identified, 113 met the inclusion criteria. Forty-nine studies reported on epidemiology, while 64 focused on mortality rates in cohorts of patients with ATTR amyloidosis from Europe (n = 16), North America (n = 26), Asia (n = 5), and Australia (n = 2). No studies were found that exclusively focused on ATTR amyloidosis in Africa or South America. ATTR prevalence ranged from 6.1/million in the US to 232/million in Portugal with very limited data on ATTR-PN. The 2-year mortality risk ranged from 10 to 30% among wild-type ATTR-CM and from 10 to 50% for variant type of ATTR-CM. Conclusions This SLR demonstrated heterogeneity in ATTR epidemiology and mortality rates across global regions. Further investigation is needed to address knowledge gaps of the epidemiology and burden of ATTR, which may improve early diagnosis and management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".